Cloud-Based AI and Data Engineering Training Course | EuroQuest International Training

The cloud is where most serious AI and data work now happens: it provides the storage, compute, and managed services that make large-scale data engineering and model deployment practical. But cloud AI brings its own disciplines, pipeline design, deployment, monitoring, cost control, and governance. This course covers them.

Participants examine cloud fundamentals across the major providers, designing data pipelines and ETL in the cloud, and deploying machine-learning models with containers and serverless approaches. The course then covers real-time and streaming analytics, closing on governance, security, compliance, and optimizing cloud cost and performance.

Why this matters

Models that work on a laptop mean nothing until they run reliably at scale on live data. Cloud data engineering is what bridges that gap, and it is where many AI initiatives stall. Professionals who can build pipelines and deploy models in the cloud turn prototypes into production, work that rests on the security foundations of the Cloud Computing and Data Analytics Integration course.

What you will be able to do afterwards

By the end of the course, participants will be able to:

Explain cloud fundamentals across AWS, Azure, and Google Cloud.
Design data pipelines for ingestion, transformation, and storage.
Deploy, monitor, and scale machine-learning models in the cloud.
Build real-time and streaming analytics.
Govern cloud AI for security, compliance, and cost.

Course outline

Unit 1: Cloud fundamentals for AI and data engineering

The unit sets out the cloud landscape.

Cloud computing essentials.
An overview of AWS, Azure, and Google Cloud.
Benefits and challenges of cloud adoption.
Case studies of AI in the cloud.

Unit 2: Data engineering in the cloud

Participants examine building the pipeline.

Designing data pipelines for big data.
Data ingestion, transformation, and storage.
Cloud tools for ETL processes.
Worked examples of pipeline creation.

Unit 3: Cloud-based AI deployment

The unit covers getting models into production.

Hosting machine-learning models on cloud platforms.
Containerization and serverless deployment.
Monitoring and scaling AI models.
A guided walkthrough of deploying a predictive model.

Unit 4: Real-time analytics and streaming data

Participants study live data.

Tools for real-time data processing.
AI applications on live data streams.
Case studies of streaming analytics in business.
A worked example with streaming data.

Unit 5: Governance, security, and the future of cloud AI

The closing unit keeps cloud AI controlled.

Data governance in cloud environments.
Compliance and risk management.
Optimizing cost and performance in cloud AI.
Future trends in cloud-based data engineering.

How the course is delivered

The course combines structured teaching with worked examples, documented cases, and guided walkthroughs of pipelines, deployment, and streaming analytics. Participants follow the path from raw data to a deployed, monitored model. The course is educational and does not provide a live cloud lab or a vendor certification.

Who should attend

The course suits data engineers and analysts, ML and AI practitioners, cloud and IT professionals, and technical managers responsible for data platforms. A working grounding in data and IT is helpful.

About EuroQuest International Training

EuroQuest International Training is an international training provider founded in 2015, with a catalog of more than 1,000 courses delivered to over 15,000 participants. Headquartered in Bratislava, EuroQuest runs courses across a network of European and regional training hubs and focuses on practical, current, and professionally relevant content.

Frequently asked questions

Is the course tied to one cloud provider?

No. It covers the concepts across AWS, Azure, and Google Cloud, so the understanding transfers wherever you work rather than teaching one vendor's console.

Why do AI projects stall at deployment?

Because a model that works on sample data still needs pipelines, monitoring, scaling, and governance to run on live data reliably. That engineering gap is exactly what this course addresses.

Does it include a live cloud lab or certification?

No. It builds understanding through worked examples and guided walkthroughs rather than a live cloud environment, and it does not confer a vendor certification.

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Register for this course

To reserve a place or request an in-house session for your team, contact EuroQuest International Training and our team will help you confirm dates and details.